Mod 4: NBA
getwd()[1] "/cloud/project"NBA = read.csv("NBA_train.csv")
str(NBA)'data.frame': 835 obs. of 20 variables:
$ SeasonEnd: int 1980 1980 1980 1980 1980 1980 1980 1980 1980 1980 ...
$ Team : chr "Atlanta Hawks" "Boston Celtics" "Chicago Bulls" "Cleveland Cavaliers" ...
$ Playoffs : int 1 1 0 0 0 0 0 1 0 1 ...
$ W : int 50 61 30 37 30 16 24 41 37 47 ...
$ PTS : int 8573 9303 8813 9360 8878 8933 8493 9084 9119 8860 ...
$ oppPTS : int 8334 8664 9035 9332 9240 9609 8853 9070 9176 8603 ...
$ FG : int 3261 3617 3362 3811 3462 3643 3527 3599 3639 3582 ...
$ FGA : int 7027 7387 6943 8041 7470 7596 7318 7496 7689 7489 ...
$ X2P : int 3248 3455 3292 3775 3379 3586 3500 3495 3551 3557 ...
$ X2PA : int 6952 6965 6668 7854 7215 7377 7197 7117 7375 7375 ...
$ X3P : int 13 162 70 36 83 57 27 104 88 25 ...
$ X3PA : int 75 422 275 187 255 219 121 379 314 114 ...
$ FT : int 2038 1907 2019 1702 1871 1590 1412 1782 1753 1671 ...
$ FTA : int 2645 2449 2592 2205 2539 2149 1914 2326 2333 2250 ...
$ ORB : int 1369 1227 1115 1307 1311 1226 1155 1394 1398 1187 ...
$ DRB : int 2406 2457 2465 2381 2524 2415 2437 2217 2326 2429 ...
$ AST : int 1913 2198 2152 2108 2079 1950 2028 2149 2148 2123 ...
$ STL : int 782 809 704 764 746 783 779 782 900 863 ...
$ BLK : int 539 308 392 342 404 562 339 373 530 356 ...
$ TOV : int 1495 1539 1684 1370 1533 1742 1492 1565 1517 1439 ...View(NBA)table(NBA$W, NBA$Playoffs)
0 1
11 2 0
12 2 0
13 2 0
14 2 0
15 10 0
16 2 0
17 11 0
18 5 0
19 10 0
20 10 0
21 12 0
22 11 0
23 11 0
24 18 0
25 11 0
26 17 0
27 10 0
28 18 0
29 12 0
30 19 1
31 15 1
32 12 0
33 17 0
34 16 0
35 13 3
36 17 4
37 15 4
38 8 7
39 10 10
40 9 13
41 11 26
42 8 29
43 2 18
44 2 27
45 3 22
46 1 15
47 0 28
48 1 14
49 0 17
50 0 32
51 0 12
52 0 20
53 0 17
54 0 18
55 0 24
56 0 16
57 0 23
58 0 13
59 0 14
60 0 8
61 0 10
62 0 13
63 0 7
64 0 3
65 0 3
66 0 2
67 0 4
69 0 1
72 0 1NBA$PTSdiff = NBA$PTS - NBA$oppPTSplot(NBA$PTSdiff, NBA$W)
WinsReg = lm(W ~ PTSdiff, data=NBA)
summary(WinsReg)
Call:
lm(formula = W ~ PTSdiff, data = NBA)
Residuals:
Min 1Q Median 3Q Max
-9.7393 -2.1018 -0.0672 2.0265 10.6026
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.100e+01 1.059e-01 387.0 <2e-16 ***
PTSdiff 3.259e-02 2.793e-04 116.7 <2e-16 ***
---
Signif. codes:
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 3.061 on 833 degrees of freedom
Multiple R-squared: 0.9423, Adjusted R-squared: 0.9423
F-statistic: 1.361e+04 on 1 and 833 DF, p-value: < 2.2e-16# Linear regression model for points scored
PointsReg = lm(PTS ~ X2PA + X3PA + FTA + AST + ORB + DRB + TOV + STL + BLK, data=NBA)
summary(PointsReg)
Call:
lm(formula = PTS ~ X2PA + X3PA + FTA + AST + ORB + DRB + TOV +
STL + BLK, data = NBA)
Residuals:
Min 1Q Median 3Q Max
-527.40 -119.83 7.83 120.67 564.71
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.051e+03 2.035e+02 -10.078 <2e-16 ***
X2PA 1.043e+00 2.957e-02 35.274 <2e-16 ***
X3PA 1.259e+00 3.843e-02 32.747 <2e-16 ***
FTA 1.128e+00 3.373e-02 33.440 <2e-16 ***
AST 8.858e-01 4.396e-02 20.150 <2e-16 ***
ORB -9.554e-01 7.792e-02 -12.261 <2e-16 ***
DRB 3.883e-02 6.157e-02 0.631 0.5285
TOV -2.475e-02 6.118e-02 -0.405 0.6859
STL -1.992e-01 9.181e-02 -2.169 0.0303 *
BLK -5.576e-02 8.782e-02 -0.635 0.5256
---
Signif. codes:
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 185.5 on 825 degrees of freedom
Multiple R-squared: 0.8992, Adjusted R-squared: 0.8981
F-statistic: 817.3 on 9 and 825 DF, p-value: < 2.2e-16summary (NBA$PTS) Min. 1st Qu. Median Mean 3rd Qu. Max.
6901 7934 8312 8370 8784 10371 # Sum of Squared Errors
PointsReg$residuals 1 2 3 4
38.5722713 142.8720040 -92.8957180 -8.3913473
5 6 7 8
-258.4705615 171.4608325 150.4081623 169.3811429
9 10 11 12
40.7756197 -75.3256614 444.9088743 94.3864704
13 14 15 16
-205.6809050 113.5969040 64.1993998 -76.5711999
17 18 19 20
249.4888007 28.0363236 329.4487991 96.3248342
21 22 23 24
349.2067913 -284.3765225 196.1611379 198.2493104
25 26 27 28
445.4100295 93.8946072 -316.2962802 -166.1909668
29 30 31 32
-5.8446359 211.2301997 155.7426615 -23.9248929
33 34 35 36
-77.9070033 218.9449693 164.1368602 -177.6479438
37 38 39 40
66.9205988 162.7892553 23.5961895 93.9839603
41 42 43 44
185.7015113 -50.2507837 -90.1181969 139.6866673
45 46 47 48
-231.1772776 111.2200135 185.9069491 210.6753018
49 50 51 52
-47.9420913 -257.8213675 225.7399197 70.4925628
53 54 55 56
432.6468031 187.4169561 -34.3947653 112.9305359
57 58 59 60
334.4717296 222.4169937 17.6755711 165.4512882
61 62 63 64
207.9970351 56.8277093 214.6051983 -23.0235142
65 66 67 68
341.7509536 -48.3807695 304.9203623 -36.7878762
69 70 71 72
-31.0357805 61.8847883 -153.0322403 121.7423324
73 74 75 76
-61.1581185 -47.9906548 -120.3599484 245.7621368
77 78 79 80
-264.3876116 161.1110819 87.3192423 426.2098591
81 82 83 84
-4.7790973 126.8613801 -97.5009340 329.9773912
85 86 87 88
-16.2338716 7.8513505 191.9280982 87.0090318
89 90 91 92
-142.5397602 -216.2264974 -199.6293933 71.0810742
93 94 95 96
257.3751407 -227.1203824 -61.4866232 71.3329444
97 98 99 100
-233.2637272 -34.7860771 84.9503466 108.6553543
101 102 103 104
-84.8168235 -90.0423121 341.2144522 52.8507112
105 106 107 108
47.8978397 181.0574099 160.7203318 237.0174702
109 110 111 112
314.9609845 51.9650831 300.2035074 -148.0931149
113 114 115 116
-13.3592416 -161.6184704 82.1172789 277.6080699
117 118 119 120
233.4334153 -225.7299932 69.0259972 37.3407430
121 122 123 124
18.2709681 121.8125335 217.9464858 -74.8210467
125 126 127 128
36.2611001 356.2366230 439.4127892 111.0266627
129 130 131 132
72.1377278 -6.1141295 331.6249450 -158.3642350
133 134 135 136
94.9048994 151.3242943 -284.7768411 -184.0287416
137 138 139 140
-103.9972773 54.1758237 139.3176593 125.3796164
141 142 143 144
-71.4407602 83.4742245 -131.6383234 -33.5752771
145 146 147 148
98.9460909 -59.8760139 -116.6711077 -110.4055752
149 150 151 152
290.8888709 38.5758792 -6.8265554 -284.8106013
153 154 155 156
149.5419209 -185.9270381 -13.5712897 -90.2301662
157 158 159 160
21.0080300 14.5295957 -346.4091267 -54.7198161
161 162 163 164
87.6823846 203.7903006 -30.7131853 -153.9699795
165 166 167 168
194.6791232 -357.4466727 133.8696823 -21.6271760
169 170 171 172
-220.4987354 -153.7269937 -383.7168614 212.2104185
173 174 175 176
-100.3118791 -30.5085767 -57.7910608 205.9463003
177 178 179 180
-124.1358862 -61.2169391 -93.9538879 -135.6180284
181 182 183 184
69.1245169 -435.5355494 -47.8153585 115.1051439
185 186 187 188
222.5411686 104.6516380 7.8335700 178.0759383
189 190 191 192
-185.3383423 122.0537263 -29.4729351 27.1344203
193 194 195 196
189.2078833 -429.5919872 57.2397301 -170.2701567
197 198 199 200
-14.0836520 21.0147294 49.6548689 -127.4633821
201 202 203 204
-87.4084020 -77.6940715 -155.2913076 8.4930328
205 206 207 208
-232.7210528 35.3384277 151.1394532 119.4563308
209 210 211 212
-416.3088878 134.8599211 33.3825347 48.4541197
213 214 215 216
-269.8021487 214.9045443 88.1318416 -24.0318730
217 218 219 220
188.2281015 -249.1537666 157.9872056 -146.6803006
221 222 223 224
72.9077663 31.1747176 337.2185582 69.7227713
225 226 227 228
-2.7440511 -55.2845827 -84.6255409 -151.4858821
229 230 231 232
234.7432200 -165.3909069 -172.9288404 386.6402387
233 234 235 236
34.4884530 -368.0387956 304.8349400 -173.0591889
237 238 239 240
168.9365987 -327.6509605 95.0370278 -75.5698743
241 242 243 244
-74.9702316 290.0371682 -21.8628806 72.5362398
245 246 247 248
-144.3565453 -44.7765529 -155.4752429 -114.0232742
249 250 251 252
82.8841506 -306.5759686 256.9630856 75.4312937
253 254 255 256
-108.9852622 -160.6985087 -1.0708625 389.4834173
257 258 259 260
48.4039145 -173.2376267 102.4859575 564.7127452
261 262 263 264
-135.6781765 435.5847710 -238.8763852 93.4120332
265 266 267 268
-346.4790813 84.2266238 124.2627684 157.9013909
269 270 271 272
90.9742388 -319.7738668 111.6330940 -136.0189613
273 274 275 276
179.6895020 -139.8481361 -60.2214721 21.1448936
277 278 279 280
-102.4930752 87.4261255 -2.2833983 -33.1839059
281 282 283 284
-313.4181662 -9.7903234 365.0041757 -170.9089658
285 286 287 288
-203.2682115 -59.0783300 344.4592952 -177.2934555
289 290 291 292
278.4424923 31.1539516 -19.4217087 146.9309508
293 294 295 296
49.6437593 323.4485389 47.1034178 3.9718411
297 298 299 300
-111.0589062 -40.0036081 187.1994351 134.5701059
301 302 303 304
-130.3795390 227.3624370 16.4481298 -91.2556101
305 306 307 308
215.9887998 70.7747666 50.5357552 -86.7616664
309 310 311 312
66.3006293 348.5847817 69.7928527 -144.9174008
313 314 315 316
48.2485248 262.5189212 -11.0182067 276.2567984
317 318 319 320
40.2609782 -235.0009787 91.8230888 -36.7029055
321 322 323 324
66.1862316 127.1446887 34.6306466 -89.1508242
325 326 327 328
-38.0350890 74.6959695 -24.6713632 -139.6322463
329 330 331 332
120.5781319 -256.3194253 35.3325803 -238.1863124
333 334 335 336
204.2701943 -231.4333870 -242.0178081 27.3589769
337 338 339 340
442.7697537 -90.3428846 -252.6536092 31.2460678
341 342 343 344
-24.0030042 -113.6697991 74.2030422 -63.3601223
345 346 347 348
13.1314540 -58.4065092 16.5093336 -26.4233092
349 350 351 352
-49.9197611 102.5295504 -276.0762358 -171.2605451
353 354 355 356
235.4118705 -295.3696087 -259.1915277 -209.8493128
357 358 359 360
-60.3803252 40.8738668 -162.3559100 -3.1584146
361 362 363 364
-252.6683460 -359.6072976 219.8480950 107.9177034
365 366 367 368
-228.4285961 77.5838841 77.6092501 176.9728823
369 370 371 372
21.0277939 225.7947949 90.6177409 -95.0387148
373 374 375 376
243.8004275 63.7765295 -135.7112041 127.9942080
377 378 379 380
208.5134149 -226.2507886 -27.4427262 215.5791874
381 382 383 384
70.0554598 -220.3324085 -252.5213694 -117.0224660
385 386 387 388
36.9146043 188.5932206 -12.6241171 24.1401960
389 390 391 392
39.4113815 130.8261623 194.8028770 140.1603242
393 394 395 396
100.4917058 367.8120506 -77.1138759 190.1907177
397 398 399 400
430.4505906 243.1092461 -220.7690501 -135.3500281
401 402 403 404
182.9169784 58.1314347 -10.3705665 134.0505987
405 406 407 408
333.4363828 110.9704334 37.1431301 188.8559358
409 410 411 412
-88.4445131 -165.3268990 148.8624801 -4.7914163
413 414 415 416
-114.6045335 -90.1562962 -65.1353805 9.9207366
417 418 419 420
-20.2393315 147.7163583 153.4474395 95.5889698
421 422 423 424
-329.6439893 323.3019593 345.3838501 -148.5288812
425 426 427 428
166.9648145 277.3541861 162.6383840 -78.9033000
429 430 431 432
-176.7932426 365.3962572 132.7242544 85.6582953
433 434 435 436
-19.3417988 95.4767236 -102.8199452 111.8183778
437 438 439 440
299.2808339 -124.0889739 -37.3805041 118.5055640
441 442 443 444
38.2173450 -122.8141423 -84.3447659 154.5643586
445 446 447 448
42.6355711 54.7178397 102.9846564 32.6861086
449 450 451 452
112.7943954 -163.3563028 150.7521084 217.5877806
453 454 455 456
-96.7133626 13.7243484 -33.1690450 -112.2550008
457 458 459 460
-15.7083565 -224.4198990 18.2593593 -393.0403979
461 462 463 464
49.2945267 52.0947949 43.2496203 -149.1223107
465 466 467 468
75.6856970 170.8878792 -257.6364448 51.6854016
469 470 471 472
11.8121415 -176.9048352 -149.5317630 -64.1990241
473 474 475 476
-71.3105611 -317.9190063 -65.8451642 97.8497015
477 478 479 480
-103.1692986 3.0848318 -104.6823532 -234.7534874
481 482 483 484
50.5295490 -75.4835788 -526.1468848 -393.9784124
485 486 487 488
-360.8366411 116.7193515 -321.3756304 -28.1090479
489 490 491 492
-508.3250405 -39.9958738 67.9854387 -97.4641720
493 494 495 496
-268.8364479 -26.0249946 188.1881640 -127.9366821
497 498 499 500
-86.3440758 133.8144538 29.4480488 -292.9821609
501 502 503 504
-124.9408024 101.3655240 -186.5181083 -63.5389375
505 506 507 508
-212.2015589 -323.1476886 -125.6610320 56.9083106
509 510 511 512
-39.0559074 -1.9339391 -319.9727619 -433.1243358
513 514 515 516
-431.1346590 -95.8909016 120.6089792 -409.7409083
517 518 519 520
-352.9341830 -527.3988939 110.6694955 -193.5043557
521 522 523 524
-92.6385367 -143.5858243 -189.7838251 172.1977457
525 526 527 528
-80.8020663 -342.9141699 124.8700974 -226.9524006
529 530 531 532
-73.5173798 -388.4868649 82.9536394 -96.7444961
533 534 535 536
-114.0835553 60.0566113 -332.3804023 -175.5276633
537 538 539 540
-338.7116370 -148.1422366 -45.2258816 -270.5159099
541 542 543 544
-159.8389177 -420.4637398 -133.0466450 183.8988039
545 546 547 548
-267.0297916 -5.2562902 -228.0471046 -11.6818058
549 550 551 552
-255.6786897 -7.7244412 -115.5357863 -298.4118693
553 554 555 556
-122.2961876 90.2924072 111.3930340 -245.4519945
557 558 559 560
-164.6445508 -29.3651223 -41.9781581 33.4260937
561 562 563 564
15.1663563 -29.4557965 44.0659204 247.9836928
565 566 567 568
-57.4318280 -238.6989443 -8.7249850 30.9454288
569 570 571 572
-343.6175905 -207.4418486 -306.4223254 157.4538406
573 574 575 576
-502.4785715 -126.1415717 48.8616098 143.9835801
577 578 579 580
-344.7694076 -116.5012114 -142.7898454 -127.9612584
581 582 583 584
-226.7659179 67.1679765 -94.0443422 -326.2414346
585 586 587 588
-84.6517620 4.5942017 -89.9757406 -97.0958454
589 590 591 592
-34.6927947 40.9701699 -88.3066869 126.5679875
593 594 595 596
-128.7529512 -166.6757304 -208.2444446 -105.4053449
597 598 599 600
-69.9961388 -104.0297252 -475.1678378 -290.6421238
601 602 603 604
195.4801727 -116.0865727 -136.0505114 -118.3811054
605 606 607 608
125.8235124 -145.2484421 -144.5655628 -435.6270621
609 610 611 612
-230.6201428 -112.7403208 -243.8883351 13.9124625
613 614 615 616
-392.1393056 -233.5727670 88.6125994 -203.7574893
617 618 619 620
-207.3393547 36.7326516 71.7237279 -110.6124268
621 622 623 624
-151.5524839 95.2365977 -227.3589026 -98.5962165
625 626 627 628
-210.8715081 -53.6787512 33.2644764 -380.2334407
629 630 631 632
-217.0512157 -135.7283167 208.5947156 -198.2473902
633 634 635 636
-147.6362401 -282.5390059 -55.4726214 3.0618526
637 638 639 640
-118.7764165 -15.9756605 1.5396468 2.2068206
641 642 643 644
-78.5559489 20.5194552 -376.9064555 -367.5790965
645 646 647 648
78.4730898 88.0528050 -178.9859105 283.6342652
649 650 651 652
18.0639226 1.4275017 -22.1910648 334.1581029
653 654 655 656
-44.6704981 -166.2133428 -112.8182784 175.7515262
657 658 659 660
60.9355144 -331.2815975 -175.1322112 34.9727118
661 662 663 664
430.8913232 -260.7815266 -99.5985786 -306.5331420
665 666 667 668
-144.2463445 -71.9561309 40.4095734 -9.9170555
669 670 671 672
9.7141807 72.8730721 -61.2840291 -51.9936086
673 674 675 676
-452.8596863 -81.9437393 69.2906290 254.7395766
677 678 679 680
-22.9459505 215.8931262 -16.9537293 -107.9068394
681 682 683 684
202.3017464 287.5765859 180.7757394 -305.5932029
685 686 687 688
56.2240459 4.5320328 -44.0648823 -278.0391307
689 690 691 692
-13.3280981 -112.7276708 422.1750569 -131.0023955
693 694 695 696
51.4971549 -86.9745423 28.8396258 -107.9302127
697 698 699 700
-55.3683153 -16.7225380 60.3453436 3.3520616
701 702 703 704
140.9429255 -17.9219329 -296.8381962 136.2394242
705 706 707 708
106.7244264 168.2861008 26.7860625 339.8954937
709 710 711 712
187.8922770 -202.6392008 148.7995083 268.8921528
713 714 715 716
0.6597544 -119.2916116 -23.0549542 -28.1758366
717 718 719 720
206.7679556 -138.5838793 -210.7824121 -29.6626073
721 722 723 724
210.3268820 -212.8798945 88.1962039 129.1032851
725 726 727 728
11.9530477 -166.3796048 -372.3297260 67.5130804
729 730 731 732
1.7122210 -179.0745146 -28.4404659 151.2765881
733 734 735 736
-425.3360446 344.3671825 -47.2592021 136.9801455
737 738 739 740
63.4427397 203.2044716 27.7908779 251.4279736
741 742 743 744
84.5817590 -155.6577645 150.3787715 138.7921016
745 746 747 748
198.4699948 101.8590582 345.8144412 35.1336113
749 750 751 752
169.1641149 354.9998851 251.7571721 47.8412497
753 754 755 756
77.9677328 66.2799291 216.7990909 155.1577399
757 758 759 760
-131.2437994 230.2449071 218.7156645 116.0349148
761 762 763 764
-78.5937100 -23.1321308 99.7713990 280.2227149
765 766 767 768
40.8527845 19.4188914 72.9388151 120.7266716
769 770 771 772
439.1035137 456.0100354 47.3239201 186.1096824
773 774 775 776
31.7505381 -54.0912550 73.0035369 234.4761589
777 778 779 780
27.9146721 -21.6493313 -75.0167664 148.4251726
781 782 783 784
106.3308316 76.0196340 37.3592068 56.5562663
785 786 787 788
-41.8917486 -200.7598142 -55.5159544 109.1518868
789 790 791 792
321.3239680 219.8866600 -73.6034103 3.1961900
793 794 795 796
-171.1408177 190.8979178 101.1845265 253.1734885
797 798 799 800
263.7840087 199.5924560 463.8379676 219.1540922
801 802 803 804
52.3032317 140.7498122 195.8267787 -55.3103142
805 806 807 808
153.8564182 61.1275837 92.8158603 -108.8302808
809 810 811 812
73.3423661 -360.6001538 134.1518035 73.3435884
813 814 815 816
141.0017271 272.8259956 -33.1611977 19.7818711
817 818 819 820
-149.9998706 190.0065593 261.3992751 308.7602526
821 822 823 824
-135.4172110 108.2677094 -171.3410196 102.4439076
825 826 827 828
156.0829202 210.0521687 109.4908936 -20.5354175
829 830 831 832
59.2845716 175.9235274 30.6531825 262.6728011
833 834 835
70.0671862 -17.5789419 -8.3393046 PointsReg2 = lm(PTS ~ X2PA + X3PA + FTA + AST + ORB + DRB + STL + BLK, data=NBA)
summary(PointsReg2)
Call:
lm(formula = PTS ~ X2PA + X3PA + FTA + AST + ORB + DRB + STL +
BLK, data = NBA)
Residuals:
Min 1Q Median 3Q Max
-526.79 -121.09 6.37 120.74 565.94
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.077e+03 1.931e+02 -10.755 <2e-16 ***
X2PA 1.044e+00 2.951e-02 35.366 <2e-16 ***
X3PA 1.263e+00 3.703e-02 34.099 <2e-16 ***
FTA 1.125e+00 3.308e-02 34.023 <2e-16 ***
AST 8.861e-01 4.393e-02 20.173 <2e-16 ***
ORB -9.581e-01 7.758e-02 -12.350 <2e-16 ***
DRB 3.892e-02 6.154e-02 0.632 0.5273
STL -2.068e-01 8.984e-02 -2.301 0.0216 *
BLK -5.863e-02 8.749e-02 -0.670 0.5029
---
Signif. codes:
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 185.4 on 826 degrees of freedom
Multiple R-squared: 0.8991, Adjusted R-squared: 0.8982
F-statistic: 920.4 on 8 and 826 DF, p-value: < 2.2e-16PointsReg3 = lm(PTS ~ X2PA + X3PA + FTA + AST + ORB + STL + BLK, data=NBA)
summary(PointsReg3)
Call:
lm(formula = PTS ~ X2PA + X3PA + FTA + AST + ORB + STL + BLK,
data = NBA)
Residuals:
Min 1Q Median 3Q Max
-523.79 -121.64 6.07 120.81 573.64
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.015e+03 1.670e+02 -12.068 < 2e-16 ***
X2PA 1.048e+00 2.852e-02 36.753 < 2e-16 ***
X3PA 1.271e+00 3.475e-02 36.568 < 2e-16 ***
FTA 1.128e+00 3.270e-02 34.506 < 2e-16 ***
AST 8.909e-01 4.326e-02 20.597 < 2e-16 ***
ORB -9.702e-01 7.519e-02 -12.903 < 2e-16 ***
STL -2.276e-01 8.356e-02 -2.724 0.00659 **
BLK -3.882e-02 8.165e-02 -0.475 0.63462
---
Signif. codes:
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 185.4 on 827 degrees of freedom
Multiple R-squared: 0.8991, Adjusted R-squared: 0.8982
F-statistic: 1053 on 7 and 827 DF, p-value: < 2.2e-16PointsReg4 = lm(PTS ~ X2PA + X3PA + FTA + AST + ORB + STL, data=NBA)
summary(PointsReg4)
Call:
lm(formula = PTS ~ X2PA + X3PA + FTA + AST + ORB + STL, data = NBA)
Residuals:
Min 1Q Median 3Q Max
-523.33 -122.02 6.93 120.68 568.26
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.033e+03 1.629e+02 -12.475 < 2e-16 ***
X2PA 1.050e+00 2.829e-02 37.117 < 2e-16 ***
X3PA 1.273e+00 3.441e-02 37.001 < 2e-16 ***
FTA 1.127e+00 3.260e-02 34.581 < 2e-16 ***
AST 8.884e-01 4.292e-02 20.701 < 2e-16 ***
ORB -9.743e-01 7.465e-02 -13.051 < 2e-16 ***
STL -2.268e-01 8.350e-02 -2.717 0.00673 **
---
Signif. codes:
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 185.3 on 828 degrees of freedom
Multiple R-squared: 0.8991, Adjusted R-squared: 0.8983
F-statistic: 1229 on 6 and 828 DF, p-value: < 2.2e-16# Compute SSE and RMSE for new model
SSE_4 = sum(PointsReg4$residuals^2)
RMSE_4 = sqrt(SSE_4/nrow(NBA))
SSE_4[1] 28421465RMSE_4[1] 184.493NBA_test = read.csv("NBA_test.csv")# Make predictions on test set
PointsPredictions = predict(PointsReg4, newdata=NBA_test)SSE = sum((PointsPredictions - NBA_test$PTS)^2)
SST = sum((mean(NBA$PTS) - NBA_test$PTS)^2)
R2 = 1 - SSE/SST
R2[1] 0.8127142RMSE = sqrt(SSE/nrow(NBA_test))
RMSE [1] 196.3723Activity 12
A. 825
B. On 7 occations teams with 38 wins can make it to the playoffs
C. 49
D. Yes, there is an upward sloping relationship
E. yes, p-valu is less than.05
F. According to the model no BLK is not significant at a 5% significance level
G. 10,371
H. we are satisfied with the value because the number is close to the real value
I. yes we are satisfied with the model
Activity 13
#WinsReg = lm(W ~ PTSdiff, data=NBA)
#49 = 41+0.0326*(x)
X_1=(49-41)/0.0326
X_1[1] 245.3988Activity 14
ThreePts_made <- c(4, 5, 3, 6, 7)
ThreePts_attmpt <- c(9, 10, 8, 11, 12)Three_pts_pct = ThreePts_made/ThreePts_attmpt
Three_pts_pct[1] 0.4444444 0.5000000 0.3750000 0.5454545 0.5833333mean(Three_pts_pct)[1] 0.4896465The average of all games is .48
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